Abstract:
In recent years, we can see the presence of CCTV cameras everywhere in developed cities and urban areas. CCTV cameras are
widely equipped in public places, buildings, and entertainment areas. Along with that popularity is the issue of effective
management and exploration of CCTV cameras to ensure security and safety for people. With a huge data recorded from cameras,
we need systems that support monitoring and analysis of camera data as well as instant video data retrieval. In this paper, we
introduce a system to contextualize the video content recorded from CCTV cameras in real time and store data efficiently. The big
data generated from the system will make it easier to monitor and operate the camera system to access and search for objects and
content in the surveillance cameras.
Download here :
https://ieeexplore.ieee.org/document/10079454
Citation:
D. -L. Pham et al., “A Deep Learning-Based Real-Time Video Object Contextualizing and Archiving System,” 2023 25th International Conference
on Advanced Communication Technology (ICACT), Pyeongchang, Korea, Republic of, 2023, pp. 137-144, doi:
10.23919/ICACT56868.2023.10079454.
keywords: {Surveillance;Urban areas;Streaming media;Big Data;Video compression;Cameras;Search problems;Video object
contextualizing;CCTV Cameras;Deep learning-based systems;Video archiving systems},
